The reality of multi-core hardware has made concurrent programs pervasive. Unfortunately, writing correct concurrent programs is difficult. Atomicity violation, which is caused by concurrent executions unexpectedly violating the atomicity of a certain code region, is one of the most common concurrency errors. However, atomicity violation bugs are hard to find using traditional testing and debugging techniques. In this paper, we investigate an approach based on machine learning techniques (specifically decision tree and support vector machine (SVM)) for classifying the benign atomicity violations from the harmful ones. A benign atomicity violation is known not to affect the program's correctness even it happens. We formulate our problem as a supervised-learning problem and apply these two machine learning techniques to classify the atomicity violation report. Our experimental evaluation shows that the proposed method is effective in identifying the benign atomicity violation warnings.

With extensive and thorough research on the three-tier B/S/D architecture and software development theory, we develop an elementary school online registration and allocation system using the bit-operation and template layered management technology in authorization management and implemented a three-tier management information system for Changchun city educational bureau, districts educational bureau to local elementary schools. In the allocation module, we propose an isometric random sample algorithm which is a fair and efficient allocation algorithm. Later, we discuss our in-depth analysis on the overall framework of the platform and each function module of the elementary school online registration and allocation system.

An interactive education information administration platform based on .NET and WAP is presented. In this platform, the users can use the WAP-capable devices such as cell phones or PDA to perform the operations such as course inquiry, grade inquiry, online registration, online sign-up and information browsing anywhere anytime they want.